In aerial imaging the surface of an object is typically imaged using an aerial imaging system freestanding from the object. For example an aerial image can be acquired by aerial photography using a camera. More specifically, aerial imaging can be used to provide an image of the ground using an elevated camera. Aerial imaging is useful in cartography, archaeology, environmental studies, tactical and strategic use by civilian and military intelligence, etc. Commonly an image acquisition system of the aerial imaging system is mounted in a flying vehicle of some kind. Examples of such are satellites orbiting the earth, and helicopters or aircrafts flying over the area to be imaged. Unmanned aerial vehicles (UAV) are also becoming more popular as they become more capable, have an endurance that outperforms manned aircraft and can be operated in harsh, or hostile, environment. Another advantage of the UAV is that aerial imaging readily can be performed in the actual area of interest. Aircraft, and in particular satellites, usually fly over the area of interest in following one direction, which is called a strip.
Each image acquired by the aerial image system usually only shows a small part of the area of interest. An overview of a larger area than can be covered by just one image frame is desirable. Furthermore, visual inspection of only one isolated image frame gives few clues to the orientation and location of the area where the image is taken and a poor overview. An improved overview can be created by stitching images together into one single image, for example an orthographic image where the image is oriented perpendicular to the ground, formed by a mosaic of single image frames. Details can then be provided by zooming in on this mosaicked image. Image stitching can also be used for panorama images by stitching together images from a stationary camera that is panned up and down (change of elevation) and moved from left to right (change of azimuth).
In a conventional aerial imaging system of an aircraft that is over-flying an area in overlapping strips, the images are matched together sequentially within one strip and further, the images of overlapping strips are matched together using so called cross strip matching, in order to generate the aerial image mosaic.
In photogrammetry, which commonly is used to produce topographic maps, geometric properties about objects are determined from photographic images. For example, the three-dimensional coordinates of points on an object are determined by measurements made in two or more photographic two-dimensional images taken from different positions or orientations. The motion described by the orientation and the location of e.g. an aircraft can be divided into two steps. First, the relative orientation of the camera between two consecutive images is determined. This is done by finding corresponding features defined by so called feature points. To correctly orient two images one needs at least four corresponding feature points. Feature selection is today mainly done manually by letting a user click on the two images and select feature points. Next, the 3D motion of the camera, the so called absolute orientation must be determined.
The matching and stitching of images are challenging operations, not least since the alignment of overlapping images to form the mosaic are computationally intensive. Conventional aerial image systems require three dimensional information of the motion of the image acquisition system to be able to perform the stitching. In satellite based acquisition systems this is simplified by having a stable predetermined tangential motion. Also in aircraft the motion pattern of the acquisition system is preferably following a linear or polar coordinate system to simplify the motion control. The motion control can be improved by using GPS signals or the like to determine the position and the altitude of the acquisition system, which also significantly reduces the computing speed of the matching operation. However, to find two neighbouring images in cross strip matching as described in the above it may not enough to use the GPS position. Two images taken from positions close to each other can view two different parts of the ground. This is due to the unknown orientation of the camera. The angular orientation of the acquisition system can be determined using gyroscopes or accelerometers. Moreover high precision cameras are required.
Aerial image systems are limited by the computational power and only a limited number of images can be matched together in a certain time period. The performance of the aerial image system, i.e. speed, image quality and mosaic size, can be improved but at the expense of increased complexity and size of the system.
In a UAV the motion pattern may be irregular, which put even higher requirements on the aerial image system. However, in opposition to the suggested improvements of the system the UAV do not allow any additional payload, rather the aerial image system should be decreased in size, weight, complexity and cost.